Empirical filter designs generalize relationships inferred from training data to effect realistic solutions that conform well to the human visual system. Complex algorithms invol...
In machine learning and computer vision, input signals are often filtered to increase data discriminability. For example, preprocessing face images with Gabor band-pass filters ...
In one-dimensional signal processing, the perfect reconstruction (PR) synthesis FB is not unique for a given analysis LP oversampled filter bank (FB). Optimal Design methods have...
In this paper we review some of our recent results on the design of critically sampled and oversampled filter banks for multiple description coding. For the case of critically sam...
Many multi-dimensional signal processing problems require the computation of signal gradients or directional derivatives. Traditional derivative estimates based on adjacent or cen...